Time-dependent genetic effects on gene expression implicate aging processes

Gene expression is dependent on genetic and environmental factors. In the last decade, a large body of research has significantly improved our understanding of the genetic architecture of gene expression. However, it remains unclear whether genetic effects on gene expression remain stable over time. Here, we show, using longitudinal whole-blood gene expression data from a twin cohort, that the genetic architecture of a subset of genes is unstable over time. In addition, we identified 2213 genes differentially expressed across time points that we linked with aging within and across studies. Interestingly, we discovered that most differentially expressed genes were affected by a subset of 77 putative causal genes. Finally, we observed that putative causal genes and down-regulated genes were affected by a loss of genetic control between time points. Taken together, our data suggest that instability in the genetic architecture of a subset of genes could lead to widespread effects on the transcriptome with an aging signature

Integrated GWAS and Gene Expression Suggest ORM1 as a Potential Regulator of Plasma Levels of Cell-Free DNA and Thrombosis Risk

Plasma cell-free DNA (cfDNA) is a surrogate marker of neutrophil extracellular traps (NETs) that contribute to immunothrombosis. There is growing interest about the mechanisms underlying NET formation and elevated cfDNA, but little is known about the factors involved. We aimed to identify genes involved in the regulation of cfDNA levels using data from the Genetic Analysis of Idiopathic Thrombophilia (GAIT-2) Project. Imputed genotypes, whole blood RNA-Seq data, and plasma cfDNA quantification were available for 935 of the GAIT-2 participants from 35 families with idiopathic thrombophilia. We performed heritability and GWAS analysis for cfDNA. The heritability of cfDNA was 0.26 ( p  = 3.7 × 10 (−6) ), while the GWAS identified a significant association (rs1687391, p  = 3.55 × 10 (−10) ) near the ORM1 gene, on chromosome 9. An eQTL (expression quantitative trait loci) analysis revealed a significant association between the lead GWAS variant and the expression of ORM1 in whole blood ( p  = 6.14 × 10 (−9) ). Additionally, ORM1 expression correlated with levels of cfDNA ( p  = 4.38 × 10 (−4) ). Finally, genetic correlation analysis between cfDNA and thrombosis identified a suggestive association ( ρ (g)  = 0.43, p  = 0.089). All in all, we show evidence of the role of ORM1 in regulating cfDNA levels in plasma, which might contribute to the susceptibility to thrombosis through mechanisms of immunothrombosis

Mapping interindividual dynamics of innate immune response at single-cell resolution

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution

Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.Peer reviewe

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

Fabrication and study of Cu contacts on large-crystalline p-type Si

94 σ.Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Μικροσυστήματα και Νανοδιατάξεις”Σκοπός της διπλωματικής εργασίας είναι η κατασκευή και μελέτη επαφών μετάλλου-ημιαγωγού (επαφών Schottky) χρησιμοποιώντας ως μέταλλα Cu και Al σε πολυκρυσταλλικό Si p-type και την παρεμβολή στην διεπιφάνεια ημιαγώγιμων υμενίων οξειδίων μεταβατικών μετάλλων και σύγκρισή τους με επαφές απουσίας αυτών.This diploma thesis is referred to the fabrication and study of Cu and Al contacts on large-crystalline p-type Si (used for the fabrication of solar cells). Thin films of transition metal oxides were inserted between the metal and the semiconductor and the resulting contacts were compared with those formed without oxides.Πανούσης Ι. Νικόλαο

Association between Ruminal pH and Rumen Fatty Acids Concentrations of Holstein Cows during the First Half of Lactation

Ruminal pH in dairy cows follows a diurnal fluctuation; low values are indicative of subacute ruminal acidosis and are associated with alterations of rumen fatty acids concentrations. The objective of the present study was to prospectively study the associations between ruminal pH and the rumen fluid concentrations of short, medium, and long chain fatty acids, under field conditions during the first half of lactation in 53 Holstein cows of a dairy farm. Ruminal fluid was obtained by rumenocentesis, which was performed at 30, 90, and 150 days in milk (DIM). Ruminal pH was measured immediately after collection with a portable pH meter, whereas gas chromatography was used for the determination of ruminal fatty acid concentrations. Mixed linear regression models were used for data analysis. The prevalence of cows with low ruminal pH (≤5.5) was 45.3%, 54.7%, and 66.0% at 30, 90, and 150 DIM, respectively. The concentrations of acetic, propionic, butyric, valeric, isovaleric, caproic and linoleic acids were negatively associated with ruminal pH values, whereas the acetic to propionic ratio was positively associated with rumen pH. Under field conditions and naturally occurring low ruminal pH cases, ruminal concentrations of most fatty acids are negatively related with ruminal pH value

MBV: a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets

Abstract Motivation Large genomic datasets combining genotype and sequence data, such as for expression quantitative trait loci (eQTL) detection, require perfect matching between both data types. Results We described here MBV (Match BAM to VCF); a method to quickly solve sample mislabeling and detect cross-sample contamination and PCR amplification bias. Availability and Implementation MBV is implemented in C ++ as an independent component of the QTLtools software package, the binary and source codes are freely available at https://qtltools.github.io/qtltools/. Supplementary information Supplementary data are available at Bioinformatics online